InfluxDB for storing machine and sensor data


Which connectors does i-flow support?

InfluxDB is a powerful open source time series database. It was specially developed for the efficient storage and retrieval of time series data.

Time series data are data points that are time-stamped and recorded continuously over time. This type of data is widely used in many applications and industries, including factory automation.


Difference between relational and time series data

Relational data is organized in a table-based structure with fixed relationships between the data records, while time series data records information in chronological order over a specific period of time.

For example, data in InfluxDB is organized in so-called “measurements”. Data points are stored in each “Measurement”, which are available as a tuple of timestamp and value.


Why time series databases?

Time series databases are specialized in processing data quickly and efficiently over time and offer a constant input speed. Optimized for fast indexing of aggregated data over time, they enable stable performance. This is particularly important in applications with continuous data growth. In contrast, relational databases become slower as the amount of data increases due to indexes.


The advantages of InfluxDB

InfluxDB is characterized by speed, scalability and a simple query language. This results in the following advantages for the industrial context, among others:

  1. Efficient storage of time series data: InfluxDB enables the efficient storage of time series data with minimal storage space requirements. At the same time, the database allows large volumes of data to be recorded and retrieved quickly.
  2. Time series data model: InfluxDB uses a special data model for time series data that enables efficient queries and aggregations. This is particularly useful for analyzing historical data and identifying trends.
  3. Scalability: InfluxDB is horizontally scalable, i.e. also suitable for environments with increasing requirements. This is an advantage because factories are dynamic and a large number of new data sources, for example, can be easily integrated.


InfluxDB in the factory

InfluxDB is successfully used in scenarios that require the continuous collection and storage of data over a longer period of time. This includes areas such as monitoring server performance, recording sensor data, monitoring the status of machines and much more. Here are a few examples:

  1. Real-time monitoring: You can record data from sensors and machines in real time in InfluxDB and analyze it with i-flow. This enables the immediate detection of deviations and problems in production.
  2. Condition monitoring: By continuously storing machine data, InfluxDB enables condition monitoring to monitor the condition of devices and systems in real time and identify anomalies or potential maintenance requirements at an early stage.
  3. Historical analysis: InfluxDB automatically stores and optionally aggregates data over time, making it possible to perform historical analysis and identify trends in production.


i-flow and InfluxDB – a powerful combination

i-flow and InfluxDB offer a powerful combination to build a reliable, secure and high-performance data infrastructure for time series data in the factory. i-flow serves as an interface to harmonize heterogeneous data from production systems and transfer it to the influxDB database. OT data (e.g. process or sensor data) can be normalized and enriched with data from other systems (e.g. control systems, sensors, databases).

While i-flow serves as the link and data processor between IT and production systems, influxDB provides the robust and secure database server for time series data.

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